Doppler Shift Based Sampling Rate Conversion for GFDM Underwater Acoustic Communication

Kumar, Virendra; Chakradhar, A.; Prasad, M. Shiva; Shekar, Y.

doi:10.1007/978-981-15-7234-0_20

Cited by 4 publications

(1 citation statement)

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“…Due to the use of the resampling technique, the computation complexity increased with the sampling rate conversion of the received signal. So, the article 17 suggested an estimation algorithm for the Doppler shift factor (DFS) is based on an oversampling technique and a sampling conversion rate algorithm to overcome the problem. The received signal's sampling rate was converted by the sampled data and linear interpolation method.…”

Section: Related Workmentioning

confidence: 99%

Energy efficient routing in IOT based UWSN using bald eagle search algorithm

Kapileswar

Kumar

2021

Trans Emerging Tel Tech

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The underwater wireless sensor network (UWSN) faces many problems such as limited bandwidth, large path loss, high attenuation, and limited battery power. In recent times, different routing protocols have been proposed in the Internet of Things (IoT) enabled UWSN (IoT-UWSNs) to explore the underwater environment for different purposes, that is, scientific and military purposes.However, high energy consumption (EC), end to end (E2E) delay, low packet delivery ratio (PDR) and minimum network lifetime make the energy efficient communication a challenging task in UWSN. The high E2E delay, EC, and reliable data delivery are the critical issues, which play an important role to enhance the network throughput. For effective achievement of EC, proposed a new routing algorithm called bald eagle search (BES). It is a nature-inspired optimization algorithm that copied bald eagle hunting behavior. The proposed routing protocol includes three stages: initialization stage, construction stage, and the data transmission phase. The nodes identify the location and the sector during the initialization process. The construction phase includes two steps, neighbor node selection, and identification of energy efficient path. Then the last phase includes the transmission, in this the broadcasting node chooses the nodes with high residual energy (RE) in comparison to the average RE of the entire network. The proposed method is implemented in MATLAB. The outcomes of simulation confirm that the BES algorithm has better performance on EC, average RE, and network lifetime than the three existing algorithm in UWSN.

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Section: Related Workmentioning

confidence: 99%